Title :
Statistical and entropy based abnormal motion detection
Author :
Lee, C.P. ; Lim, K.M. ; Woon, W.L.
Author_Institution :
Fac. of Inf. Sci. & Technol., Multimedia Univ., Ayer Keroh, Malaysia
Abstract :
As visual surveillance systems are gaining wider usage in a variety of fields, they need to be embedded with the capability to interpret scenes automatically, which is known as human motion analysis (HMA). However, existing HMA methods are too domain specific and computationally expensive. This paper proposes a general purpose HMA method. It is based on the idea that human beings tend to exhibit random motion patterns during abnormal situations. Hence, angular and linear displacements of limb movements are characterized using basic statistical quantities. In addition, it is enhanced with the entropy of the Fourier spectrum to measure the randomness of the abnormal behavior. Various experiments have been conducted and prove that the proposed method has very high classification accuracy in identifying anomalous behavior.
Keywords :
Fourier transforms; entropy; image motion analysis; statistical analysis; Fourier spectrum; abnormal motion detection; angular displacement; human motion analysis; limb movement; linear displacement; motion pattern; statistical quantity; visual surveillance system; Entropy; Image Processing; Motion Analysis; Neural Networks;
Conference_Titel :
Research and Development (SCOReD), 2010 IEEE Student Conference on
Conference_Location :
Putrajaya
Print_ISBN :
978-1-4244-8647-2
DOI :
10.1109/SCORED.2010.5704000